Intraday futures breakout using an alternative signal set
Backtest results · hypothetical, not live
Alternative signals, 2020–2026
Performance
Detail
Results from a single backtest on QuantConnect. Costs and slippage modeled per the strategy's deployment specification.
About
A variant of the intraday futures breakout family that uses a different signal architecture from the standard index breakout model. Where the standard model defines its breakout levels from intraday volatility, this version constructs its entry conditions from a distinct set of market signals. Both operate on the same underlying instruments and share the same intraday-flat discipline: every trade is closed by the session close.
The core backtest runs from 2020 through August 2026 and produces a Sharpe of 1.32 with 54% CAGR and 26.6% max drawdown. Win rate is 32%, and the average win is 3.7x the average loss. The combination of a low win rate and a large win-to-loss ratio is characteristic of a breakout strategy that accepts many small stops in exchange for infrequent but large trending moves. Those figures are net of modeled commissions and slippage on every fill, which matters more here than anywhere else on the site: see the execution-cost note below.
This is included as a separate entry from the standard intraday index breakout because the signal logic is architecturally different. The two strategies share instrument overlap but have low return correlation, making them candidates for ensemble combination rather than substitutes. Currently in live simulation, returning +7% so far.
Execution costs
Intraday strategies live or die on execution. A model that holds for weeks pays its costs a handful of times a year. This one pays them on every entry and every exit, hundreds of times a year, so a cost assumption that is even slightly too kind can manufacture an edge that does not exist. Nothing shown above is a gross figure. Costs are charged inside the backtest, trade by trade, before any statistic is computed.
Each fill is charged an Interactive Brokers retail commission, per contract on futures and per share on ETFs, and charged per side, so a round turn pays twice. Retail pricing, not an institutional rate I do not actually get.
On top of commissions, every fill is moved against the strategy by a slippage adjustment before the trade is booked. Buys fill worse than the modeled price, and so do sells. The adjustment is sized to cover the bid-ask spread and queue position on the instruments actually traded.
The platform default for stop fills runs optimistic for breakout strategies, because stops trigger in exactly the fast conditions where fills are worst. I compare modeled fills against my own broker fills on the same signals and tighten the assumption until the backtest matches what I actually get.
The win rate, loss rate, average win, and average loss shown above are all post-cost measurements. Costs push each result toward the losing side: a trade that finished a tick or two ahead gross ends up recorded as a small loss, winners are booked slightly smaller than the price move, and losers slightly larger. So the win rate you see is lower than the raw signal produces, and the ratio between the average win and the average loss is narrower.
That matters most for a low win-rate breakout strategy, where the arithmetic depends on a small number of large wins covering many small losses. Shrink the wins and inflate the losses on every trade and the whole structure can invert. Reading these statistics as already-degraded numbers is the point: the margin between the average win and the average loss is what survives the cost model, not what the signal looks like before it.
This is also why some intraday strategies I have built are not on this site. They cleared every other test and then failed this one. The exact commission and slippage parameters, and the validation stages each strategy has to pass, are written up in full on the methodology page.